) Using the SILVERSPRING data set, develop a multiple linear regression model to predict asking price based on assessed value, size and number of bedrooms. a) Interpret the meaning of the slope coefficients. b) Use the regression model to find the predicted asking price of a house with an assessed value of 600,000, 3,000 square feet and 5 bedrooms. Also find the corresponding prediction and confidence interval. c) Interpret the meaning of the coefficient of multiple regression. d) At the 0.05 significance level, determine if there is a significant relationship between asking price and the three independent variables. e) At the 0.05 significance level, determine whether each independent variable makes a significant contribution to the regression model. 2) Do 14.81 from textbook, parts a, b, c, e, g, h ( just look at r2), i 3) The following is the linear regression model predicting college GPA based on weekly study hours x1, high school GPA x2 and SAT score x3. y = 0.02×1 + 0.75×2 + 0.0001×3 a) Interpret the meaning of the slope coefficients. b) Use the model to predict the college GPA of a student who studies 20 hours per week, had a high school GPA of 4.2 and a combined SAT of 1350. 4) Assume a simple linear regression model. Given the predicted value of y when x equals 5 is 10 and the predicted value of y when x equals 6 is 13, find the value of the slope coefficient b1. 4) Assume a simple linear regression model. Given b0 = 95.6, find the value of y when x = 0.